Package edu.cmu.tetrad.search.work_in_progress

Interface ISScore

All Known Implementing Classes:

ISBDeuScore, ISBicScore

public interface ISScore

Interface for a score suitable for FGES

Method Summary

Modifier and Type	Method	Description
boolean	determines(List<Node> z, Node y)	Determines whether the given list of nodes has a specific relationship with the specified node.
DataSet	getDataSet()	Retrieves the dataset used in the scoring calculations.
int	getMaxDegree()	Retrieves the maximum allowable degree for nodes in the current scoring context.
double	getSamplePrior()	Retrieves the prior probability assigned to the sample.
int	getSampleSize()	Retrieves the sample size used in the score computation.
double	getStructurePrior()	Retrieves the prior value assigned to the structure.
Node	getVariable(String targetName)	Retrieves a variable node by its target name.
List<Node>	getVariables()	Retrieves a list of variables represented as nodes.
boolean	isEffectEdge(double bump)	Determines whether the edge has a significant effect based on the given bump value.
double	localScore(int node, int[] parents_is, int[] parents_pop, int[] children_population)	Calculates the local score for a given node in the context of its parent nodes and children population.
double	localScore1(int node, int[] parents_is, int[] parents_pop, int[] children_pop)	Calculates the local score for a given node in the context of its parent nodes and children population, without using structure prior.
double	localScoreDiff(int x, int y, int[] parentsY_is, int[] parentsY_pop, int[] childrenY_pop)	Calculates the difference between local scores before and after introducing a change in the relationship between nodes x and y, considering their parent and children populations.
void	setSamplePrior(double samplePrior)	Sets the prior probability value assigned to the sample.
void	setStructurePrior(double structurePrior)	Sets the prior value assigned to the structure.

Method Details

localScore

double localScore(int node,
 int[] parents_is,
 int[] parents_pop,
 int[] children_population)

Calculates the local score for a given node in the context of its parent nodes and children population.

Parameters:

node - The index of the node for which the score is being calculated.

parents_is - An array representing the indices of the parent nodes.

parents_pop - An array representing the population of the parent nodes.

children_population - An array representing the population of the children nodes.

Returns:

The local score for the specified node.

localScoreDiff

double localScoreDiff(int x,
 int y,
 int[] parentsY_is,
 int[] parentsY_pop,
 int[] childrenY_pop)

Calculates the difference between local scores before and after introducing a change in the relationship between nodes x and y, considering their parent and children populations.

Parameters:

x - The index of the node x.

y - The index of the node y.

parentsY_is - An array of indices representing the parent nodes of y.

parentsY_pop - An array of indices representing the population of parent nodes of y.

childrenY_pop - An array of indices representing the population of children nodes of y.

Returns:

The difference in local scores due to the relationship change between x and y.

getVariables

List<Node> getVariables()

Retrieves a list of variables represented as nodes.

Returns:

A list of nodes representing the variables.

isEffectEdge

boolean isEffectEdge(double bump)

Determines whether the edge has a significant effect based on the given bump value.

Parameters:

bump - The threshold value to evaluate the significance of the effect on the edge.

Returns:

true if the edge has a significant effect; false otherwise.

getSampleSize

int getSampleSize()

Retrieves the sample size used in the score computation.

Returns:

the sample size.

getVariable

Node getVariable(String targetName)

Retrieves a variable node by its target name.

Parameters:

targetName - the name of the target variable to retrieve

Returns:

the node representing the variable with the specified target name

getMaxDegree

int getMaxDegree()

Retrieves the maximum allowable degree for nodes in the current scoring context.

Returns:

The maximum degree a node can have.

determines

boolean determines(List<Node> z,
 Node y)

Determines whether the given list of nodes has a specific relationship with the specified node.

Parameters:

z - the list of nodes to be evaluated.

y - the node to be checked against the list.

Returns:

true if the list of nodes determines the specified node; false otherwise.

localScore1

double localScore1(int node,
 int[] parents_is,
 int[] parents_pop,
 int[] children_pop)

Calculates the local score for a given node in the context of its parent nodes and children population, without using structure prior.

same as localSCire but this one doesn't use structure prior

Parameters:

node - The index of the node for which the score is being calculated.

parents_is - An array representing the indices of the parent nodes.

parents_pop - An array representing the population of the parent nodes.

children_pop - An array representing the population of the children nodes.

Returns:

The local score for the specified node.

getStructurePrior

double getStructurePrior()

Retrieves the prior value assigned to the structure.

Returns:

the structure prior value as a double.

setStructurePrior

void setStructurePrior(double structurePrior)

Sets the prior value assigned to the structure.

Parameters:

structurePrior - the structure prior value to be set as a double.

getSamplePrior

double getSamplePrior()

Retrieves the prior probability assigned to the sample.

Returns:

the sample prior value as a double.

setSamplePrior

void setSamplePrior(double samplePrior)

Sets the prior probability value assigned to the sample.

Parameters:

samplePrior - the sample prior value to be set as a double.

getDataSet

DataSet getDataSet()

Retrieves the dataset used in the scoring calculations.

Returns:

the dataset used in the scoring calculations.